Clostridium difficile is a hospital infection that disproportionately affects immunosuppressed patients, including those undergoing chemotherapy and the elderly, and can in some cases be fatal. Research shows FMT treatment is often the best option for those suffering from recurrent infection.

Before FMT treatment can be administered, donors must be carefully screened to ensure best results in the target patients and achieve optimum quantities of essential bacteria for sample preparation. However, a limitation of this is being able to accurately identify and select the best colonies, due to their often tenacious nature. Automating these processes reduces observation errors and biases due to human vision and heuristics, creating a level of consistency and accuracy that wouldn’t be possible with hand-picking.

Treatment for C. diff infection

Clostridium difficile (C. diff) is an anaerobic bacteria that can colonise the gut microbiome. It is estimated that C. diff makes up roughly 2% of gut flora but it is not traditionally considered part of the gut microbiome, it exists in both toxigenic and non-toxigenic forms but it is toxigenic forms that cause issues [1]. C. diff infection (CDI) usually happens when people have taken a course of antibiotics or have weakened immune systems due to another condition or treatment such as chemotherapy. C. diff symptoms are widely associated with severe gastrointestinal problems and fever, and had a mortality rate of 3.4 deaths per 100,000 people in the UK 2021-22 [2].

The current treatment for C. diff is a strong round of antibiotics, usually vancomycin for severe cases of CDI and metronidazole for mild cases [3]. After treatment with antibiotics recurrence of infection is common due to further gut dysbiosis, therefore focus is shifting onto restoring normal gut microbial flora [4]. The development of novel therapeutics for CDI has led to research into bacteriophage-derived endolysins as an alternative to antibiotics [5].

However, there are issues with delivery, in research, they have only been delivered by oral gavage, which isn’t advantageous in practice as the chance of C. diff resistance is high. Faecal microbiota transplant (FMT) is the administration of a faecal sample from a healthy donor to another person with gut dysbiosis and has been successful in the treatment of recurrent C. diff infection [6]. FMT is currently the best therapeutic option for recurrent CDI, especially where treatment with antibiotics has failed [7]. There are currently two FMT treatments with FDA approval, first Rebyota (2022) and then Vowst (2023). More research is needed as these are very expensive and there are difficulties with administration, only Vowst can be given orally [8].

Benefits of PIXL

Colony Imaging

PIXL’s five fluorescence channels and a white light channel can be used to consistently identify diverse bacteria by phenotype and morphotype.

For example, C. diff has intrinsic green and blue autofluorescence when excited with blue/ultraviolet light in aerobic conditions [9]. PIXL can be used to excite and then image samples to quantify the success of treatments. Relative fluorescence is also used as a marker for gene expressions, such as by using fluorescent LOV domains for C.diff in anaerobic environments [9]. Identify C. diff in GFP studies can be further achieved using fluorescent biomarkers such as mCherry for the measurement of localisation and gene expression of C. diff [10].

Further applications of PIXL for colony imaging:

• Export rich phenotypic data for each colony, with annotations.
• Automatically generate barcodes for each plate, or alternatively plug in a barcode scanner, ensuring end-to-end data traceability.
• Either way the barcodes will be shown in the data export so you can fully track your plates.
• Create libraries of raw and processed images, keeping track of plates in extended workflows, perfect for high throughput analysis.
• Quantify antimicrobial properties using PIXL’s Zone of Inhibition software to automatically detect, analyse zones of clearing, and pick central colonies.

Figure 1. ZOI software on PIXL, is being used to identify central colonies and measure overlapping antimicrobial zones.

Colony Counting

Accurate colony counting and CFU is essential to measure the effectiveness of CDI treatment by measuring C.diff in stool samples from patients. PIXL’s automated colony counting, accurate to 50 microns, can be used in standard protocols within C. diff research, such as:

• Random mutagenesis screening.
C. diff CFU in stool samples after a round of antibiotics.
• Quantification of C. diff toxin gene expression TcdA and TcdB [11].

Colony Picking

Bacterial production strains used for FMT must be correctly identified to prevent the introduction of a harmful infection into the recipient. However, manually picking desired colonies can be repetitive, time-consuming and labour-intensive.

Improve patient safety by employing PIXL to:

• Identify faecal bacteria useful for the development of FMT: PIXL is able to pick diverse colonies with a pinning transfer efficiency of 99.78%.
• Pick central colonies with PIXL’s new Zone of Inhibition software.
• Automate anaerobic colony picking by putting PIXL into an anaerobic chamber.
• Maintain sterility and eliminate contamination with disposable tips in a single PickupLine. This supports PIXL’s compatibility within an anaerobic chamber as it removes the requirement of changing picking tips, autoclaving and refitting them, and the associated downtime.
• Increase throughput by combining PIXL with a robotic arm for reliable walk-away automation.

Picking from Agar plate to PCR

The evaluation of how effective treatments are in clinical trials, using samples to show shedding of C. diff during and after treatment for CDI. PCR-ribotyping is used for the genotyping of C. diff from faecal samples but C. diff needs to be isolated first [12]. With PIXL you can automate this process and pick target C. diff colonies from a standard plate straight into PCR plates, ready for ribotyping.

Alternatively, PIXL can also be used to pick from multiwell plates to a MALDI-TOF MS plate for microbial identification. This improves reproducibility of sample preparation and makes processes easier for less experienced users.

Figure 2. PIXL software showing a target PCR plate.

colony pick with the standard PIXL set up


Is for users looking to automate manual colony picking with an intuitive and user-friendly robot.

PIXL in Anerobic Chamber with automated setup

PIXL with Anaerobic Chamber

A customised anaerobic chamber designed for PIXL with user experience in mind, making integration seamless.


[1] Vedantam, G et al, (2012). Clostridium difficile infection.

[2] GOV.UK. (2023). 30 day all-causemortality following MRSA, MSSA and Gram-negative bacteraemia and C. difficile infections: 2021 to 2022 report.

[3] Bagdasarian, N et al (2019). Diagnosisand Treatment of Clostridium difficile in Adults: A Systematic Review.

[4] Zhang, Y et al (2022). The development of live biotherapeutics against Clostridioides difficile infection towards reconstituting gut microbiota.

[5] Mondal, SI et al, (2020). Bacteriophage endolysins as a potential weapon to combat Clostridioides difficile infection.

[6] Gupta, S et al, (2016). Fecal microbiota transplantation: in perspective.

[7] Cho, YS. (2021). Fecal Microbiota Transplantation Is Effective for the Treatment of Partially Treated Clostridioides difficile Infection.

[8] FitzGerald M, Young A. (2023). Gut check: The FDA approves microbiome-based therapies, with future approvals expected.

[9] Buckley M, et al (2016). LightingUp Clostridium Difficile: Reporting Gene Expression Using Fluorescent Lov Domains.

[10] Ransom EM, et al (2015). Use of mCherry Red fluorescent protein for studies of protein localization and gene expression in Clostridium difficile.

[11] Chumbler NM, et al (2016) – Clostridium difficile Toxins TcdAand TcdB Cause Colonic Tissue Damage by Distinct Mechanisms.

[12] Sethi AK, et al (2015). Persistence of Skin Contamination and Environmental Shedding of Clostridium difficile during and after Treatment of C. difficile Infection.